almost implemented k

README.md

@@ -8,3 +8,27 @@ machine learning server, for image classification
  - For the input images, calculates the euclidean distances
  - Gets the nearest neighbour
  - Show the result, that is the label of the object in the image
+
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+
+
+-------------
+
+send file over ssh:
+```
+scp dataset.tar.gz root@51.255.193.106:/root/galdric
+```
+
+on the server, untar file:
+```
+tar -xvzf dataset.tar.gz
+```

knn.go

@@ -1,5 +1,10 @@
 package main
 
+import (
+	"fmt"
+	"sort"
+)
+
 func euclideanDist(img1, img2 [][]float64) float64 {
 	var dist float64
 	for i := 0; i < len(img1); i++ {
@@ -11,17 +16,55 @@ func euclideanDist(img1, img2 [][]float64) float64 {
 	return dist
 }
 
+type Neighbour struct {
+	Dist  float64
+	Label string
+}
+
+func isNeighbour(neighbours []Neighbour, dist float64, label string) []Neighbour {
+	var temp []Neighbour
+
+	for i := 0; i < len(neighbours); i++ {
+		temp = append(temp, neighbours[i])
+	}
+	ntemp := Neighbour{dist, label}
+	temp = append(temp, ntemp)
+
+	//now, sort the temp array
+	sort.Slice(temp, func(i, j int) bool {
+		return temp[i].Dist < temp[j].Dist
+	})
+
+	for i := 0; i < len(neighbours); i++ {
+		neighbours[i] = temp[i]
+	}
+
+	return neighbours
+}
+
 func knn(dataset Dataset, input [][]float64) string {
-	d := euclideanDist(dataset["leopard"][0], input)
+	k := 3
-	label := "lamp"
+	var neighbours []Neighbour
-	for k, v := range dataset {
+	//d := euclideanDist(dataset["leopard"][0], input)
+	for i := 0; i < k; i++ {
+		/*neighbours[i].Dist = euclideanDist(dataset["leopard"][0], input)
+		neighbours[i].Label = "leopard"*/
+		neighbours = append(neighbours, Neighbour{euclideanDist(dataset["leopard"][0], input), "leopard"})
+	}
+	for l, v := range dataset {
 		for i := 0; i < len(v); i++ {
 			dNew := euclideanDist(v[i], input)
-			if dNew < d {
+			/*if dNew < d {
 				d = dNew
-				label = k
+				label = l
+			}*/
+			neighbours = isNeighbour(neighbours, dNew, l)
 		}
 	}
+	for i := 0; i < len(neighbours); i++ {
+		fmt.Print(neighbours[i].Label + " - ")
+		fmt.Println(neighbours[i].Dist)
 	}
-	return label
+
+	return neighbours[0].Label
 }

tests.sh

@@ -0,0 +1,5 @@
+curl -F file=@./leop2.jpg http://127.0.0.1:3055/image
+
+curl -F file=@./test2.jpg http://127.0.0.1:3055/image
+
+curl -F file=@./test.jpg http://127.0.0.1:3055/image